class_docstr: A class for generating signals from streamlines in an efficient and speedy
  manner.
docstr: Approximate the signal for a given streamline
docstr_tok: ["Approximate","the","signal","for","a","given","streamline"]
code: def streamline_signal(self, streamline):
      """
      Approximate the signal for a given streamline
      """
      grad = streamline_gradients(streamline)
      sig_out = np.zeros((grad.shape[0], self.signal.shape[-1]))
      for ii, g in enumerate(grad):
          sig_out[ii] = self.calc_signal(g)
      return sig_out
  
imports: import numpy
  import scipy.sparse
  import scipy.linalg
  from dipy.reconst.base import ReconstModel, ReconstFit
  from dipy.tracking.utils import unique_rows
  from dipy.tracking.streamline import transform_streamlines
  from dipy.tracking.vox2track import _voxel2streamline
  import dipy.data
  import dipy.core.optimize
label_desc: Use image node_id 3 for calling the LifeSignalMaker obj's underlying member method code with example usage: obj.streamline_signal(streamline) and returns: sig_out